Gathering information through household surveys about prescription drug use and spending is much more difficult than for some other kinds of medical services. While most people can readily recall, for example, whether they were hospitalized in the last year and for what reason, filling a prescription is not so memorable an event. People who filled only one or two prescriptions may not remember them at all. Those who had many medications may not recall just how many they had or may not be able to name every drug they were taking. Even people who can accurately report what drugs they used may not be able to tell what those drugs cost. This is especially true when the drug cost is covered by an insurer or a public program; the respondent may know only the amount of his or her required copayment, not the total charge.

The MEPS and MCBS surveys use a variety of techniques to overcome these barriers to collection of complete and accurate information about prescription drugs. The following is a brief overview of how the two surveys go about answering two key questions:

How many prescriptions did participants fill during the period covered by the survey?

What was paid for those drugs, including both out-of-pocket payments by the respondents and payments by insurers or other third parties?

The MCBS and the MEPS household component both involve multiple rounds of interviews with each respondent. In each interview, the respondent is asked about services used in the period since the last interview. MEPS separately surveys pharmacies named by respondents, and can thus supplement the information gathered in the household survey. Because MCBS has no pharmacy component, it must collect all utilization and price information through the household survey.

MCBS uses a variety of devices to promote fuller reporting by participants. Between interviews, participants are asked to keep track of the services they used on a calendar and to retain bills, receipts, check stubs and other relevant documentation. For a filled prescription they are asked to save and bring to the interview the actual bottle, the package it came in, and any receipts or other statements they received with the prescription. To further aid recall, the interviewer in each round has information about the drugs reported in the previous interview, and thus can ask whether the respondent is still taking the same drugs. Still, the information is probably incomplete. Some respondents may not keep the requested records, or the proxy who actually participates in the survey for individuals unable to be interviewed may not have full information.

MEPS collects less information through the household survey. For example, charge and payment data are not obtained from participants who report that their insurance pays the pharmacy directly. Instead, MEPS obtains some information through the pharmacy component. Each participant who reports having a prescription is asked to identify the pharmacy that filled it and to give permission for that pharmacy to share information. Permission was obtained for 73 percent of possible person-pharmacy pairs, and pharmacies responded to data requests for 67 percent of these pairs. Thus there is information from pharmacies for about half the instances in which a participant named a specific pharmacy.

The pharmacy component provided more detailed data on specific drugs used and on their costs, but it did not actually increase MEPS estimates of total drug utilization. It was expected that pharmacies would sometimes report filling more prescriptions for an individual than the individual had reported in the household survey. While this sometimes occurred, aggregate utilization estimates derived from the household data alone are actually larger than those derived from the pharmacy survey alone. Thus there remains the possibility of some undercounting of total prescriptions. However, aggregate MEPS data benchmark fairly well to external data on prescription drug utilization.

The MEPS data, based on household responses supplemented with some reporting from pharmacies, can be compared to IMS data, which are based on pharmacy audits. MEPS estimates a total of 2.1 billion prescriptions, excluding free samples, for the noninstitutionalized population in 1996. IMS data show total pharmacy prescription volume of 2.41 billion, about 15 percent more. However, the IMS data include prescriptions for people in institutions, including the 1.6 million people who were in nursing homes in 1996 and who are often heavy users of prescription drugs. MEPS excluded people in institutions (along with individuals in the military, prisoners, and non-resident individuals). The difference in populations covered may account for much of the difference in total prescription counts.

For the Medicare population, MEPS reports 9.8 percent more prescriptions than does MCBS. The two surveys are almost identical in their estimates of the proportion of beneficiaries who received any prescription during the year; the difference is chiefly in their estimates of the annual number of prescriptions for each person who received any prescription drug. A portion of this difference is attributable to somewhat different treatment of diabetic supplies in MEPS and MCBS. The MEPS estimate includes expenditures for insulin and diabetic supplies totaling nearly $2 billion. MCBS includes insulin in prescription drug expenditures, but excludes diabetic supplies. Insulin purchases do not require a prescription, but a prescription is generally needed to receive third party payments.

Because the focus in this report is on relative utilization by the covered and noncovered populations, whether the MCBS prescription count is complete is less important than whether the possible undercount is more serious for one or the other of these groups. This is difficult to ascertain, however, because of the differences in assignment of coverage status between MEPS and MCBS. MCBS reports more prescriptions than MEPS for beneficiaries without coverage and fewer for beneficiaries with coverage. This is probably partially attributable to the fact that MCBS treats as noncovered some beneficiaries who used prescription drugs and would have been assigned coverage under MEPS on the basis of a third-party payment. Since people with coverage tend to have higher utilizaton than those without coverage, having peole with coverage in the noncovered category will tend to raise estimates of average spending and utilization for the noncovered category.

MEPS data for 1996 indicate that 27 percent of people who used prescription drugs paid for those drugs in full at the time they received them.3 Most people with public or private coverage pay only a copayment or coinsurance amount. (Exceptions include people who have not yet met a deductible or who have exceeded a cap on their coverage and people who have an indemnity plan, which reimburses the policyholder instead of the pharmacy.) As a result, household survey data alone can provide cost information for only a portion of all prescriptions.

Because MEPS has a pharmacy component, it can obtain full price information for prescriptions paid for by third parties. As noted earlier, however, pharmacy survey responses were not always available. When neither the individual nor a pharmacy provided price data for a prescription, the price had to be imputed through statistical matching: a total price was assigned to the prescription based on price data for the same drug furnished to a similar individual. There were also instances in which a total price was available for the prescription, but the amounts paid by the insurer and/or the individual were missing. Again, values were imputed for each such prescription.

MCBS also uses a process of imputation in cases in which household respondents were unable to supply price and payment information. Because MCBS has no pharmacy component, imputation is needed for more prescriptions than under MEPS, and the method of assigning prices is different.4 The MCBS average price per non-Medicaid prescription, $35.23, is quite close to the average price of $35.90 found by MEPS for Medicare beneficiaries without Medicaid.5 However, because MCBS counts fewer prescriptions per beneficiary using prescription drugs, its aggregate spending estimates are lower than MEPS estimates for Medicare beneficiaries.

Because the process of imputation leads to some potential measurement errors in comparing prices paid for a particular drug by individuals with different coverage statuses, all the price comparisons in chapter 3 are based on MEPS drug purchases for which the price was established through a direct match of pharmacy and household survey information. However, for the spending estimates in chapter 2, both the MCBS and the MEPS data used include prescriptions for which prices were imputed. Dropping all prescriptions for which prices were imputed would have left nationally unrepresentative populations and samples too small to estimate aggregate spending differences for different subgroups. Imputation is designed to generate accurate aggregate estimates, but may misrepresent pricing, especially for individual drugs.

It should be emphasized that all of the MEPS spending information, and most of that under MCBS, reflects only the amounts paid to pharmacies.6 These amounts are not adjusted for any rebates that may be paid by the manufacturer to the insurer, because these rebates are generally not reflected in the prices charged at the point of sale. There is one exception: under MCBS, but not MEPS, spending data for Medicaid beneficiaries are reduced to reflect rebates received from manufacturers by state Medicaid programs. Rebate estimates are derived from state financial reports to HCFA(now known as CMS). Thus, all other things being equal, we would expect aggregate spending estimates for MCBS to be somewhat lower than for MEPS.

As was discussed earlier, MEPS produces higher estimates of Medicare beneficiaries who had drug coverage than MCBS for three basic reasons. First, MEPS assigns coverage to larger numbers of people who did not report having drug coverage but who were found to have a third-party payment for a prescription. Second, MEPS treats all Medicaid and Medicare risk HMO enrollees as having drug coverage, although in fact not all do. Third, MCBS screens out beneficiaries whose reported coverage is inconsistent with their payment history. Each of these differences has potential implications for estimates of relative spending by covered and noncovered beneficiaries.

While the availability of payment-source data from pharmacies increases the coverage estimates under MEPS relative to those under MCBS, the method necessarily misses people with drug coverage who failed to report it and who did not have any drug expenditure during the year. These people remain in the noncovered group, while the people assigned to coverage on the basis of a drug expenditure are by definition all utilizers of drugs. This biases utilization and spending estimates upward for the population treated as covered and downward for the noncovered group, widening differences between the two groups.

This effect is partially offset by the MEPS assignment of drug coverage to all Medicaid beneficiaries and Medicare HMO enrollees. MCBS finds lower utilization by beneficiaries in these groups who did not have a drug benefit. Their inclusion in the MEPS counts of covered people thus depresses the MEPS estimates of spending for people with coverage.

Finally, MCBS treats as noncovered those beneficiaries who reported having coverage but paid more than $250 out of pocket and reported no insurance payment, while MEPS leaves these beneficiaries in the covered category. The effect is to raise the MEPS estimates of out-of-pocket spending for covered people and to lower the estimates for noncovered people. This effect does not appear to be very large.

In combination, these factors mean that MEPS data show larger utilization and spending differences between covered and noncovered beneficiaries than those shown in the MCBS data used in chapter 2. This would merely reinforce the key point of that chapter, that insurance has an important effect on use of prescription drugs. The MEPS data would also show a larger proportion of covered beneficiaries, and a smaller proportion of noncovered ones, receiving any prescription drugs at all.

MEPS and MCBS also differ in their estimates of out-of-pocket spending by Medicare beneficiaries. They are close in their estimates of the proportion of total spending that is paid out of pocket, 47 percent under MCBS and 50 percent under MEPS. However, MCBS finds beneficiaries with coverage paying about 33 percent of their own expenses, compared to 43 percent under MEPS. This difference is partially attributable to the differences in coverage estimates described above. However, the difference persists for groups, such as those with employer coverage, for whom the MEPS and MCBS coverage estimates are quite close. Further investigation will be needed to fully account for this difference. Use of the MEPS data would have shown smaller differences in out- of-pocket spending for people with and without coverage than are shown in chapter 2. As a corollary, however, MEPS data show that many people who have coverage have insurance that leaves them exposed to high out-of-pocket costs.

It should be emphasized that, while some aspects of the MEPS method of assigning coverage may introduce potential biases into its estimates of relative utilization by covered and noncovered beneficiaries, there is no reason to believe that chapter 3 overstates the price differences for the two groups. It was noted earlier that, while MEPS treats as having drug coverage people who failed to report coverage but had a third-party payment, there was no way of identifying people who failed to report their coverage and who received no drugs during the year. For the purpose of pricing comparisons, the omission of the latter group from the covered category does not affect the results (since they had no prescription to price). There does remain the issue of treating all Medicaid beneficiaries and Medicare HMO enrollees as having drug coverage. Some noncovered people in these populations have been included in the covered category. However, because people without coverage routinely pay more for their prescriptions than people with coverage, the probable result is that the MEPS data understate rather than overstate price differentials for the covered and noncovered.

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